Disease Surveillance

Infectious diseases, though initially tend to be limited geographically to a reservoir; a subsequent spatial variation in disease prevalence (including spread & intensity) arises from the underlying differences in physical-biological conditions that support pathogen, its vectors & reservoirs. Different factors like spatial proximity, physical & social connectivity, & local environmental conditions which add to its susceptibility influence the occurrence[2]. In Disease management, analysis of historical data over various aspects of geography, epidemiology, social structures & network dynamics need to be accounted for. Large amounts of data raise issues of data processing, storage, pattern identification, etc. In addition, identifying the source of disease occurrence & its pattern can be of immense value. ST-DM of disease data can be an effective tool for endemic preparedness[3], as it extracts implicit knowledge, spatial & temporal relationships, or other patterns inherent in such databases. Here, Core Region is defined as a set of spatial entities(eg.counties) aggregated over time, which occur frequently at places having high values in a defined region (considering areas of influence around them)[1].

Objective:

This work leverages spatio-temporal data mining (ST-DM), the MiSTIC (Mining Spatio-Temporally Invariant Cores)[1,6] method for infectious disease surveillance, by identifying a) Extent of spatial spread of disease core regions across populations-scale of disease prevalence b) Possible causes of the observed patterns-for better prediction, detection & management of infectious disease & its outbreaks.

Surveillance of risky behaviors of HIV infection and its manifest diseases has provided a better understanding of the complex nature of the HIV epidemic in India. However, little attempt is made to analyze progress of these surveillance activities.

Objective

To study and analyze the surveillance activities in HIV prevention and control in India.

The multivariate linear-time subset scan (MLTSS) extends previous spatial and subset scanning methods  to achieve timely and accurate event detection in massive multivariate datasets, efficiently optimizing a likelihood ratio statistic over proximity-constrained subsets of locations and all subsets of the monitored data streams. However, some disease outbreaks may only affect a subpopulation of the monitored population (age group, gender, individuals engaging in a specific high-risk behavior, etc.), and MLTSS is unable to use this additional information to enhance detection ability.

Objective

We present Multidimensional Subset Scan (MD-Scan), a new method for early outbreak detection and characterization using multivariate case data from individuals in a population. MD-Scan extends previous work on multivariate event detection by identifying the characteristics of the affected subpopulation, and enables more timely and accurate detection while maintaining computational tractability

Pertussis (i.e., whooping cough) is on the rise in the US. To implement effective prevention and treatment strategies, it is critical to conduct timely contact tracing and evaluate people who may have come into contact with an infected person. We describe a collaborative effort between epidemiologists and public health informaticists at the Utah Department of Health (UDOH) to determine the feasibility and value of a network-analytic approach to pertussis outbreak management and contact tracing.

Objective: 

To determine the feasibility and value of a social network analysis tool to support pertussis outbreak management and contact tracing in the state of Utah.

 

Effective responses to epidemics of infectious diseases hinge not only on early outbreak detection, but also on an assessment of disease severity. In recent work, we combined previously developed ARI case-detection algorithms (CDA) [1] with text analyses of chest imaging reports to identify ARI patients whose providers thought had pneumonia. In this work, we asked if a surveillance system aimed at patients with pneumonia would outperform one that monitors the full severity spectrum of ARI.

Objective

To determine if influenza surveillance should target all patients with acute respiratory infections (ARI) or only track pneumonia cases.

 

Surveillance to track the incidence, prevalence and treatment of disease is a fundamental task of public health. The advent of universal health care coverage in the United States and electronic health records could make the medical record a valuable disease surveillance tool. This can only happen, however, if the necessary data can be extracted from the medical record without manual review.

Objective

The objective of this project was to identify criteria that accurately categorize acute coronary and heart failure events exclusively with electronic health record data so that the medical record can be used for surveillance without manual record review.

 

The international Society for Disease Surveillance has successfully brought together practitioners and researchers to share tools, ideas, and strategies to strengthen health surveillance systems. The Society has evolved from an initial focus on syndromic surveillance to a broader consideration of innovation in health surveillance. More recently, ISDS has also worked to support surveillance research and practice in International resource-constrained settings. Individuals who work in surveillance in developed countries outside the USA, however, have received little direct attention from ISDS. The policy and practice contexts in these countries are often quite different than the USA, so there is a need to support surveillance innovation in these countries in a manner that fits the context. Canadian surveillance practitioners and researchers comprise the largest International group of ISDS members, and these members have expressed an interest in working with ISDS to translate surveillance innovations into practice in Canada, where a national surveillance network and forum is lacking. This Round Table will consider how ISDS can help to support members in countries like Canada and will identify next steps for promoting the science and practice of disease surveillance in the Canadian context.

Objective

1) To explore how ISDS can better support researchers and public health practitioners working in the field of disease surveillance outside the United States;

and

2) To identify current surveillance issues in the Canadian public health system where ISDS can support dialogue and action.

 

Major global stakeholder groups including the United Nations, World Health Organization and Institute of Medicine seek to raise awareness of the threat to global health and security of chronic and non-communicable diseases. These conditions comprise 50-85% of the global annual morbidity burden and constitute a major drain on national economies. To move from awareness of this problem to action and amelioration of issues, we need effective means for monitoring and intervening with populations using approaches that span primary, secondary and tertiary prevention.

Objective

To characterize current and future approaches to surveillance of chronic and non-communicable diseases and establish the agenda for both methodological and condition-specific progress.